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Ethnicity and Population Structure in Personal Naming Networks

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  • Pablo Mateos
  • Paul A Longley
  • David O'Sullivan

Abstract

Personal naming practices exist in all human groups and are far from random. Rather, they continue to reflect social norms and ethno-cultural customs that have developed over generations. As a consequence, contemporary name frequency distributions retain distinct geographic, social and ethno-cultural patterning that can be exploited to understand population structure in human biology, public health and social science. Previous attempts to detect and delineate such structure in large populations have entailed extensive empirical analysis of naming conventions in different parts of the world without seeking any general or automated methods of population classification by ethno-cultural origin. Here we show how ‘naming networks’, constructed from forename-surname pairs of a large sample of the contemporary human population in 17 countries, provide a valuable representation of cultural, ethnic and linguistic population structure around the world. This innovative approach enriches and adds value to automated population classification through conventional national data sources such as telephone directories and electoral registers. The method identifies clear social and ethno-cultural clusters in such naming networks that extend far beyond the geographic areas in which particular names originated, and that are preserved even after international migration. Moreover, one of the most striking findings of this approach is that these clusters simply ‘emerge’ from the aggregation of millions of individual decisions on parental naming practices for their children, without any prior knowledge introduced by the researcher. Our probabilistic approach to community assignment, both at city level as well as at a global scale, helps to reveal the degree of isolation, integration or overlap between human populations in our rapidly globalising world. As such, this work has important implications for research in population genetics, public health, and social science adding new understandings of migration, identity, integration and social interaction across the world.

Suggested Citation

  • Pablo Mateos & Paul A Longley & David O'Sullivan, 2011. "Ethnicity and Population Structure in Personal Naming Networks," PLOS ONE, Public Library of Science, vol. 6(9), pages 1-12, September.
  • Handle: RePEc:plo:pone00:0022943
    DOI: 10.1371/journal.pone.0022943
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    References listed on IDEAS

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    1. Lambiotte, Renaud & Blondel, Vincent D. & de Kerchove, Cristobald & Huens, Etienne & Prieur, Christophe & Smoreda, Zbigniew & Van Dooren, Paul, 2008. "Geographical dispersal of mobile communication networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(21), pages 5317-5325.
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    Cited by:

    1. Crescenzi, Riccardo & Nathan, Max & Rodríguez-Pose, Andrés, 2016. "Do inventors talk to strangers? On proximity and collaborative knowledge creation," Research Policy, Elsevier, vol. 45(1), pages 177-194.
    2. Shi, Yongbin & Li, Le & Wang, Yougui & Chen, Jiawei & Stanley, H. Eugene, 2019. "A study of Chinese regional hierarchical structure based on surnames," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 518(C), pages 169-176.
    3. Lansley, Guy & Longley, Paul, 2016. "Deriving age and gender from forenames for consumer analytics," Journal of Retailing and Consumer Services, Elsevier, vol. 30(C), pages 271-278.
    4. Kai On Wong & Osmar R Zaïane & Faith G Davis & Yutaka Yasui, 2020. "A machine learning approach to predict ethnicity using personal name and census location in Canada," PLOS ONE, Public Library of Science, vol. 15(11), pages 1-16, November.
    5. Alberto Acerbi & Vasileios Lampos & Philip Garnett & R Alexander Bentley, 2013. "The Expression of Emotions in 20th Century Books," PLOS ONE, Public Library of Science, vol. 8(3), pages 1-6, March.
    6. Jung, Jay Heon & Kumar, Alok & Lim, Sonya S. & Yoo, Choong-Yuel, 2019. "An analyst by any other surname: Surname favorability and market reaction to analyst forecasts," Journal of Accounting and Economics, Elsevier, vol. 67(2), pages 306-335.
    7. Muhammad Adnan & Paul Longley, 2013. "Featured Graphic. Tweets by Different Ethnic Groups in Greater London," Environment and Planning A, , vol. 45(7), pages 1524-1527, July.
    8. Jens Kandt & Paul A Longley, 2018. "Ethnicity estimation using family naming practices," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-24, August.
    9. Stefano Breschi & Francesco Lissoni & Gianluca Tarasconi, 2014. "Inventor Data for Research on Migration and Innovation: A Survey and a Pilot," WIPO Economic Research Working Papers 17, World Intellectual Property Organization - Economics and Statistics Division.
    10. Paul A Longley & Muhammad Adnan & Guy Lansley, 2015. "The Geotemporal Demographics of Twitter Usage," Environment and Planning A, , vol. 47(2), pages 465-484, February.
    11. Neil Cummins, 2022. "The hidden wealth of English dynasties, 1892–2016," Economic History Review, Economic History Society, vol. 75(3), pages 667-702, August.

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